Shaobo Lin

发表

Optimal Learning Rates for Kernel Partial Least Squares

Ding-Xuan Zhou, Shaobo Lin, 2018 .

Learning theory of distributed spectral algorithms

Ding-Xuan Zhou, Shaobo Lin, Zheng-Chu Guo, 2017 .

Is Extreme Learning Machine feasible ? A Theoretical Assessment ∗

Zongben Xu, Shaobo Lin, Xia Liu, 2013 .

A convergence rate for approximate solutions of Fredholm integral equations of the first kind

Zongben Xu, Shaobo Lin, F. Cao, 2012 .

Alibaba-AIC : Submission to Multi-Moments in Time Challenge 2019 ∗

C. Li, Shaobo Lin, Biao Wang, 2019 .

Distributed learning with multi-penalty regularization

Lei Shi, Shaobo Lin, Zheng-Chu Guo, 2017, Applied and Computational Harmonic Analysis.

Learning rates of regularized regression on the unit sphere

Zongben Xu, Shaobo Lin, F. Cao, 2013 .

Multivariate Jackson-type inequality for a new type neural network approximation

Shaobo Lin, Yuanhua Rong, Zongben Xu, 2014 .

Cubature formula for spherical basis function networks

Zongben Xu, Shaobo Lin, F. Cao, 2012 .

A Cyclic Coordinate Descent Algorithm for lq Regularization

Zhimin Peng, Zongben Xu, Shaobo Lin, 2014, 1408.0578.

A Unified Framework with Meta-dropout for Few-shot Learning

Xingyu Zeng, Shaobo Lin, Rui Zhao, 2022, 2210.06409.

A convergence rate for approximate solutions of Fredholm integral equations of the first kind

Zongben Xu, Shaobo Lin, F. Cao, 2011, Positivity.

Learning rates of regularized regression on the unit sphere

Zongben Xu, Shaobo Lin, F. Cao, 2012, Science China Mathematics.

Cubature formula for spherical basis function networks

Zongben Xu, Shaobo Lin, F. Cao, 2012, Chinese Annals of Mathematics, Series B.

Approximation by neural networks with scattered data

Zongben Xu, Feilong Cao, Shaobo Lin, 2013, Appl. Math. Comput..

The essential rate of approximation for radial function manifold

Feilong Cao, Shaobo Lin, Zongben Xu, 2011 .

Greedy Criterion in Orthogonal Greedy Learning

Xia Liu, Yi Fang, Zongben Xu, 2016, IEEE Transactions on Cybernetics.

Shrinkage Degree in $L_{2}$ -Rescale Boosting for Regression

Zongben Xu, Yao Wang, Shaobo Lin, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Deep Neural Network Based Vehicle and Pedestrian Detection for Autonomous Driving: A Survey

Hangbin Wu, Dongpu Cao, Shaobo Lin, 2021, IEEE Transactions on Intelligent Transportation Systems.

Essential rate for approximation by spherical neural networks

Zongben Xu, Feilong Cao, Shaobo Lin, 2011, Neural Networks.

Simultaneous approximation by spherical neural networks

Feilong Cao, Shaobo Lin, Shaobo Lin, 2016, Neurocomputing.

Error Estimate for Spherical Neural Networks Interpolation

Zongben Xu, Jinshan Zeng, Shaobo Lin, 2015, Neural Processing Letters.

A general radial quasi-interpolation operator on the sphere

Zongben Xu, Feilong Cao, Xiangyu Chang, 2012, J. Approx. Theory.

L p Error Estimates for Scattered Data Interpolation On Spheres

Feilong Cao, Shaobo Lin, Shaobo Lin, 2011 .

The capability of approximation for neural networks interpolant on the sphere

Feilong Cao, Shaobo Lin, Shaobo Lin, 2010 .

Divide and Conquer Local Average Regression pdf

Yao Wang, Xiangyu Chang, Shaobo Lin, 2016, ArXiv.

Sparse Regularization: Convergence Of Iterative Jumping Thresholding Algorithm

Zongben Xu, Jinshan Zeng, Shaobo Lin, 2014, IEEE Transactions on Signal Processing.

Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part I)

Xia Liu, Zongben Xu, Jian Fang, 2015, IEEE Trans. Neural Networks Learn. Syst..

Construction of Neural Networks for Realization of Localized Deep Learning pdf

Charles K. Chui, Ding-Xuan Zhou, Shaobo Lin, 2018, Front. Appl. Math. Stat..

The estimate for approximation error of spherical neural networks

Feilong Cao, Shaobo Lin, Huazhong Wang, 2011 .

Approximation capability of interpolation neural networks

Zongben Xu, Feilong Cao, Shaobo Lin, 2010, Neurocomputing.

Learning Through Deterministic Assignment of Hidden Parameters

Zongben Xu, Jian Fang, Shaobo Lin, 2018, IEEE Transactions on Cybernetics.

Prediction-based Termination Rule for Greedy Learning with Massive Data.

Runze Li, Chen Xu, Jian Fang, 2016, Statistica Sinica.

Almost optimal estimates for approximation and learning by radial basis function networks

Zongben Xu, Shaobo Lin, Xia Liu, 2014, Machine Learning.

Does generalization performance of l q regularization learning depend on q ? A negative example ∗ pdf

Chen Xu, Jinshan Zeng, Jian Fang, 2014 .

Rescaled Boosting in Classification

Yao Wang, Xu Liao, Shaobo Lin, 2019, IEEE Transactions on Neural Networks and Learning Systems.

Explore the Power of Synthetic Data on Few-shot Object Detection

Xingyu Zeng, Shaobo Lin, Kun Wang, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

An Effective Crop-Paste Pipeline for Few-shot Object Detection

Xingyu Zeng, Shaobo Lin, Kun Wang, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

A Novel Two-path Backbone Network for Object Detection

Long Chen, Yue Sun, Shaobo Lin, 2020, 2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL).

Interpolation and Best Approximation for Spherical Radial Basis Function Networks

Jinshan Zeng, Shaobo Lin, Zongben Xu, 2013 .

Learning capability of the truncated greedy algorithm

Zongben Xu, Shaobo Lin, Lin Xu, 2016, Science China Information Sciences.

Regularization: Convergence of Iterative Half Thresholding Algorithm

Zongben Xu, Jinshan Zeng, Yao Wang, 2014 .

Sparse solution of underdetermined linear equations via adaptively iterative thresholding pdf

Zongben Xu, Jinshan Zeng, Shaobo Lin, 2013, Signal Process..

Greedy metrics in orthogonal greedy learning pdf

Zongben Xu, Jinshan Zeng, Lin Xu, 2014, ArXiv.

Learning and approximation capabilities of orthogonal super greedy algorithm pdf

Zongben Xu, Jian Fang, Shaobo Lin, 2014, Knowl. Based Syst..

Learning Rates for Classification with Gaussian Kernels

Jinshan Zeng, Xiangyu Chang, Shaobo Lin, 2017, Neural Computation.

High-Resolution Driving Scene Synthesis Using Stacked Conditional Gans and Spectral Normalization

Long Chen, Wei Tian, Qin Zou, 2019, 2019 IEEE International Conference on Multimedia and Expo (ICME).

L1/2 Regularization: Convergence of Iterative Half Thresholding Algorithm

Zongben Xu, Shaobo Lin, Jinshan Zeng, 2013, ArXiv.

Learning Rates of lq Coefficient Regularization Learning with Gaussian Kernel

Zongben Xu, Jinshan Zeng, Jian Fang, 2013, Neural Computation.

Distributed Learning with Regularized Least Squares pdf

Ding-Xuan Zhou, Shaobo Lin, Xin Guo, 2016, J. Mach. Learn. Res..

Distributed Kernel-Based Gradient Descent Algorithms

Ding-Xuan Zhou, Shaobo Lin, Ding-Xuan Zhou, 2018 .

Distributed Semi-supervised Learning with Kernel Ridge Regression

Xiangyu Chang, Ding-Xuan Zhou, Shaobo Lin, 2017, J. Mach. Learn. Res..

Unified Low-Rank Matrix Estimate via Penalized Matrix Least Squares Approximation

Xiangyu Chang, Yao Wang, Shaobo Lin, 2019, IEEE Transactions on Neural Networks and Learning Systems.

Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part I)

Xia Liu, Zongben Xu, Jian Fang, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Constructive Neural Network Learning

Xiaoqin Zhang, Jinshan Zeng, Shaobo Lin, 2016, IEEE Transactions on Cybernetics.

A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning pdf

Yuan Yao, Jinshan Zeng, Shaobo Lin, 2019, ArXiv.

Global Convergence of Block Coordinate Descent in Deep Learning

Yuan Yao, Jinshan Zeng, Shaobo Lin, 2018, ICML.

L 1/2 Regularization: Convergence of Iterative Half

Zongben Xu, Shaobo Lin, Jinshan Zeng, 2013 .

Fast Learning With Polynomial Kernels

Jinshan Zeng, Shaobo Lin, Shaobo Lin, 2019, IEEE Transactions on Cybernetics.

Learning Capability of Relaxed Greedy Algorithms

Zongben Xu, Xingping Sun, Shaobo Lin, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Model selection of polynomial kernel regression pdf

Zongben Xu, Jinshan Zeng, Xingping Sun, 2015, ArXiv.

Re-scale boosting for regression and classification pdf

Yao Wang, Lin Xu, Shaobo Lin, 2015, ArXiv.

Global Convergence in Deep Learning with Variable Splitting via the Kurdyka-{\L}ojasiewicz Property

Tim Tsz-Kit Lau, Y. Yao, Shaobo Lin, 2018 .

Nonparametric regression using needlet kernels for spherical data pdf

Shaobo Lin, Shaobo Lin, 2015, J. Complex..

Constructive approximate interpolation by neural networks in the metric space

Zongben Xu, Feilong Cao, Shaobo Lin, 2010, Math. Comput. Model..

Learning capability of the truncated greedy algorithm

Zongben Xu, Lin Xu, Shaobo Lin, 2016, Science China Information Sciences.

Global Convergence of Block Coordinate Descent in Deep Learning

Tim Tsz-Kit Lau, Y. Yao, Shaobo Lin, 2018, ICML.

Block Coordinate Descent for Deep Learning: Unified Convergence Guarantees pdf

Yuan Yao, Jinshan Zeng, Shaobo Lin, 2018, ArXiv.

On ADMM in Deep Learning: Convergence and Saturation-Avoidance

Ding-Xuan Zhou, Yuan Yao, Shaobo Lin, 2019, J. Mach. Learn. Res..

Learning Through Deterministic Assignment of Hidden Parameters

Zongben Xu, Shaobo Lin, Jian Fang, 2018, IEEE Transactions on Cybernetics.